MétaCan
Menu
Back to cohort
Record W4407418509 · doi:10.1093/ijnp/pyae059.183

PHARMACOGENETIC TESTING IN TREATMENT-RESISTANT PANIC DISORDER: A PILOT STUDY

2025· article· en· W4407418509 on OpenAlexaff
Rafael C. Freire, Marcos Fidry, Morena Mourao Zugliani, Mariana Costa do Cabo, Clara V. Faria, Antônio Egídio Nardi

Bibliographic record

VenueThe International Journal of Neuropsychopharmacology · 2025
Typearticle
Languageen
FieldMedicine
TopicHormonal Regulation and Hypertension
Canadian institutionsKingston Health Sciences CentreKingston General HospitalQueen's University
Fundersnot available
KeywordsPanic disorderPharmacogeneticsPanicPsychologyClinical psychologyMedicinePsychiatryGenotypeAnxietyGeneticsBiologyGene

Abstract

fetched live from OpenAlex

Abstract Background Pharmacological treatment is considered effective in the treatment of panic disorder (PD). However, about 20 to 40% of PD patients do not respond to the first pharmacological treatment. Trials with multiple drugs are often required before response to treatment is achieved. Pharmacogenetic testing is a promising new tool to aid clinicians in finding the right medication and the right dose for each patient. It could be especially useful in the treatment of treatment-resistant patients with PD. Aims and Objectives Ascertain the usefulness of pharmacogenetic testing in treatment-resistant PD. Methods 20 PD patients who did not respond to treatment-as-usual (TAU) were included in this study. Only patients who were on medications with known efficacy for PD, on adequate dose, and received treatment for at least 8 weeks were considered eligible. Patients with Clinical Global Impression – Improvement (CGI-I) of 1 (very much improved) or 2 (much improved) were considered responders, patients with scores higher than 2 were considered non-responders. The key enzymes’ genetic polymorphisms evaluated were: CYP2D6, CYP2C19, CYP2C9, CYP1A2, CYP3A4, CYP3A5, CYP2B6, FKBP5, HTR2A, ANKK1, HTR1A, HTR2C, DRD2, GRIK4, ADRA2A, OPRM1, COMT, SLC6A4 e ABCB1, FKBS, GSK3B, EPHX1, UGT1A4, UGT2B15, MC4R, SCN1A, SLC6A4, MTHFR (rs1801131 e rs1811133). We retrospectively compared the recommendations of the pharmacogenetic analysis with the treatment the patient actually received. Results The recommendation from the pharmacogenetic analysis regarding the actual prescribed drug was “use according to the label” in 40% of the cases, “use with attention” in 55% of the cases and “use with caution and attention” in 5% of the cases. Pharmacogenetic testing indicated reduced chance of response to the prescribed drug in 30% of the subjects, while they indicated very low serum levels of the prescribed drug (fast metabolism) in 20% of the subjects. The CYP3A4 and CYP2D6 activity was normal for most patients. CYP2C19 phenotype indicated slower enzyme activity in 25%, faster enzyme activity in 40%, and normal enzyme activity in 35% of patients. The pharmacogenetic tests predicted a small reduction of methylenetetrahydrofolate reductase (MTHFR) enzyme activity in 75% of the patients. Discussion and Conclusion If the pharmacogenetic was made before the treatment, if would have interfered on the medication choice and changed treatment outcome only in 5% of the subjects. Since the polymorphism associated with low MTHFR activity was very prevalent, this finding raises the question of a possible association between this polymorphism and treatment resistance in PD. Low MTHFR activity was associated with treatment resistance in mood disorders. Administering L-methylfolate would bypass the enzyme and correct the vitamin deficiency in the intracellular level, making these patients treatment responsive. Given the findings from the current study, pharmacogenetic tests would not have aided clinicians in finding the right pharmacological treatments for each patient. High prevalence of CYP2C19 and MTHFR polymorphisms in PD patients requires further study. References Baldwin, D.S., Anderson, I.M., Nutt, D.J., Allgulander, C., Bandelow, B., Den Boer, J.A., Christmas, D.M., Davies, S., Fineberg, N., Lidbetter, N., Malizia, A., McCrone, P., Nabarro, D., O’ Neill, C., Scott, J., Van Der Wee, N., Wittchen, H.U., 2014. Evidence-based pharmacological treatment of anxiety disorders, post- traumatic stress disorder and obsessive-compulsive disorder: A revision of the 2005 guidelines from the British Association for Psychopharmacology. J. Psychopharmacol. 28, 403–439. https://doi.org/10.1177/0269881114525674 Bjelland, I., Tell, G.S., Vollset, S.E., Refsum, H., Ueland, P.M., 2003. Folate, vitamin B12, homocysteine, and the MTHFR 677C→ T polymorphism in anxiety and depression. The Hordaland Homocysteine Study. Arch. Gen. Psychiatry. https://doi.org/10.1001/archpsyc.60.6.618 Blaya, C., Salum, G.A., Lima, M.S., Leistner-Segal, S., Manfro, G.G., 2007. Lack of association between the Serotonin Transporter Promoter Polymorphism (5-HTTLPR) and Panic Disorder: a systematic review and meta-analysis. Behav Brain Funct 3, 41. https://doi.org/1744-9081-3-41 [pii]\n10.1186/1744-9081-3- 41 Caldirola, D., Perna, G., 2015. Is there a role for pharmacogenetics in the treatment of panic disorder? Pharmacogenomics. https://doi.org/10.2217/pgs.15.66 Freire, R.C., Hallak, J.E., Crippa, J.A., Nardi, A.E., 2011. New treatment options for panic disorder: clinical trials from 2000 to 2010. Expert Opin. Pharmacother. https://doi.org/10.1517/14656566.2011.562200 Froese, D.S., Huemer, M., Suormala, T., Burda, P., Coelho, D., Gué ant, J.L., Landolt, M.A., Kož ich, V., Fowler, B., Baumgartner, M.R., 2016. Mutation Update and Review of Severe Methylenetetrahydrofolate Reductase Deficiency. Hum. Mutat. https://doi.org/10.1002/humu.22970 He, Q., Mei, Y., Liu, Y., Yuan, Z., Zhang, J., Yan, H., Shen, L., Zhang, Y., 2019. Effects of Cytochrome P450 2C19 Genetic Polymorphisms on Responses to Escitalopram and Levels of Brain-Derived Neurotrophic Factor in Patients with Panic Disorder. J. Clin. Psychopharmacol. https://doi.org/10.1097/JCP.0000000000001014

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.059
GPT teacher head0.379
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueThe International Journal of NeuropsychopharmacologySame topicHormonal Regulation and HypertensionFrench-language works237,207